US 11,990,216 B2
Detecting discrepancies between clinical notes and administrative records
Yufan Guo, San Jose, CA (US); David J. Beymer, San Jose, CA (US); Tyler Baldwin, Culver City, CA (US); Vandana Mukherjee, Mountain View, CA (US); and Tanveer F. Syeda-Mahmood, Cupertino, CA (US)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Nov. 29, 2022, as Appl. No. 18/070,615.
Application 18/070,615 is a continuation of application No. 16/514,485, filed on Jul. 17, 2019, granted, now 11,574,713.
Prior Publication US 2023/0095258 A1, Mar. 30, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G16H 10/60 (2018.01); G06F 16/335 (2019.01)
CPC G16H 10/60 (2018.01) [G06F 16/335 (2019.01)] 21 Claims
OG exemplary drawing
 
1. A method, in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a discrepancy detection mechanism for detecting discrepancies between clinical notes and administrative records, wherein the discrepancy detection mechanism operates to:
extracting clinical concepts from the clinical notes and the administrative records in a patient's electronic medical records (EMRs) at least by imposing a lexicon-based algorithm with inexact matching of clinical terms with the capacity of identifying contiguous and non-contiguous concepts;
filtering the extracted clinical concepts based on semantic type information to identify concepts that reference diseases or syndromes while also removing negated instances;
utilizing the positive mentions of diseases in clinical notes, comparing the positive mentions of diseases or syndromes in the clinical notes against each positive entry in the administrative records; and
generating a discrepancy summary for diseases or syndromes that failed to translate correctly from clinical notes to the administrative records in the patient's EMRs.